基于一次成像测量FRET系统校正因子的智能型QuanTi-FRET方法

Automatic QuanTi-FRET Method for Measuring System Correction Factors Based on Single Imaging

QuanTi-FRET是一种通过对多种荧光共振能量转移(FRET)标准质粒样本进行多次FRET成像来测量FRET成像系统敏化淬灭转化因子(G)和供受体通道激发效率校正因子(β)的方法。本课题组发展了一种基于一次成像测量系统校正因子G和β的智能型QuanTi-FRET方法———AutoQT-FRET方法。AutoQT-FRET方法包括如下4个步骤:1)将分别转染了不同FRET标准串联质粒(C5V、C17V、C32V和CTV)的细胞合并到一个细胞培养皿中培养,对该皿细胞样本进行三通道FRET成像;2)对三通道图像进行区域划分,并根据不同种类的FRET标准质粒对各区域进行归类;3)对归类成功的区域逐像素绘制三维空间散点图,以确定各个FRET标准质粒的标准线;4)使用确定好的各质粒标准线对整个视野内的细胞区域进行质粒分类与系统校正因子G和β的测量。该方法大幅简化了系统校正因子的测量过程,缩短了测量时间。本文比较了AutoQT-FRET方法与其他方法测量系统校正因子的优劣,实验结果表明:AutoQT-FRET方法操作简单,而且测量稳定性与准确度都有所提高。

Objective Quantitative fluorescence resonance energy transfer(FRET) is an important technology that can be used to study molecular interactions in living cells, analyze the molecular structure of oligomerized proteins, and study regulatory mechanisms between proteins in signal pathways. A prerequisite for quantitative FRET detection technology is determining the correction factor of the FRET measurement system. Among many system calibration factors, the system calibration factor(G) related to the inherent performance of the instrument and fluorescent molecules is particularly important. However, traditional methods, such as the donor-dequenching method, TP-G method, and two hybrid-multi plasmid methods, are cumbersome. The QuanTi-FRET method can measure the sensitized quenching transition factor(G) and the donor and the acceptor excitation correction factor(β) of a FRET imaging system by performing multiple FRET imaging for different types(≥3) of standard FRET plasmid samples. However, this method is challenged by the difficulty in switching multi-dish cells to measure different types(≥3) of standard FRET plasmid samples and thus ensuring the same contrast and background signals when imaging multi-dish cell samples separately. In this study, we have developed an automatic QuanTi-FRET method(AutoQT-FRET) to measure the G and β factors by measuring cells that express multiple FRET standard plasmids with different FRET efficiencies in a cell petri dish. We hope that our method can be helpful for researchers using quantitative FRET technology.Methods In this study, quantitative FRET and living-cell fluorescence imaging were performed using our multimodal FRET microscopy imaging system, mainly consisting of an inverted wide-field fluorescence microscope(IX73, Olympus, Japan) and a high-sensitivity CMOS camera(ORCA-Flash 4.0, Hamamatsu, Japan). The Auto QT-FRET method contains four steps:(1) Combine the cells transfected with different types of FRET standard tandem plasmids(C5V, C17V, C32V, and CTV) into one cell petri dish to perform three-channel imaging.(2) Divide the three-channel image into regions, and classify regions using different FRET standard plasmids.(3) Draw a threedimension spatial scatter map pixel-by-pixel for the successfully classified regions to determine the plasmid standard line.(4) Use the plasmid standard line to classify the plasmid, and measure the G and β values in the cell regions of the entire field of vision.Results and Discussions In this study, the IDD-Fc images of standard FRET plasmids with different FRET efficiencies have different ranges of slope k that do not intersect each other. The k value ranges of the four standard FRET plasmids(C5V, C17V, C32V, and CTV) were listed in Table 1. Using the Auto QT-FRET, we classified cells transfected with multiple standard FRET plasmids in a cell petri dish and labeled them with different colors [Fig.3(a)]. Simultaneously, the Auto QT-FRET method classified cells transfected with multiple standard FRET plasmids in one cell petri dish and accurately divided the cell boundaries of overlapping cells transfected with different standard FRET plasmids [Fig.3(b)]. In Fig.3(b), we accurately classified two overlapping cells transfected with different standard FRET plasmids, and the red and green cells were transfected with C5V and C32V plasmids, respectively. Furthermore, we used the classification results of the cells transfected with multiple standard FRET plasmids in one cell petri dish to measure the correction factor G using the TP-G, TH-M, and Auto QT-FRET methods. As the TP-G method only needs double plasmids, we selected TP-G-1(C5V and CTV), TP-G-2(C17V and CTV), and TP-G-3(C32V and CTV) groups to analyze, and the correction factor G values were 5.34±1.63, 3.99±1.39, and 3.01±1.27. The large error of the result shows that the TP-G method may not be the best method for getting correction factor G. Thereafter, we used the Auto QT-FRET and TH-M methods to analyze the same cell data. Based on the TH-M and Auto QT-FRET methods, the system correction factor G values were obtained as 3.72±0.93 and 3.51±0.81, respectively(Fig.4). It shows that the TH-M and Auto QT-FRET methods have similar stability in calculating the correction factor G. Conclusions We developed an automatic Quan T-FRETi(Auto QT-FRET) method to measure the G and β factors by performing single imaging. The method for transfecting multiple plasmids in one cell dish reduces the time and shortens the process of calculating the correction factor G of the system. Simultaneously, the Auto QT-FRET method can classify cells transfected with multiple standard FRET plasmids in a cell petri dish. Thus, it enables the accurate measurement of the system correction factors G and β values using the one-button operation of one-time imaging of a cell petri dish, which greatly simplifies data processing and lowers the threshold for researchers who use quantitative FRET measurements. The Auto QT-FRET method is not only robust but also fast and concise.